Inference for copula modeling of discrete data: a cautionary tale and some facts

Olivier P. Faugeras. "Inference for copula modeling of discrete data: a cautionary tale and some facts." Dependence Modeling 5.1 (2017): 121-132. <http://eudml.org/doc/288496>.

@article{OlivierP2017,
abstract = {In this note, we elucidate some of the mathematical, statistical and epistemological issues involved in using copulas to model discrete data. We contrast the possible use of (nonparametric) copula methods versus the problematic use of parametric copula models. For the latter, we stress, among other issues, the possibility of obtaining impossible models, arising from model misspecification or unidentifiability of the copula parameter.},
author = {Olivier P. Faugeras},
journal = {Dependence Modeling},
keywords = {copula; discrete data; parametric model; statistical inference; unidentifiability},
language = {eng},
number = {1},
pages = {121-132},
title = {Inference for copula modeling of discrete data: a cautionary tale and some facts},
url = {http://eudml.org/doc/288496},
volume = {5},
year = {2017},
}

TY - JOUR
AU - Olivier P. Faugeras
TI - Inference for copula modeling of discrete data: a cautionary tale and some facts
JO - Dependence Modeling
PY - 2017
VL - 5
IS - 1
SP - 121
EP - 132
AB - In this note, we elucidate some of the mathematical, statistical and epistemological issues involved in using copulas to model discrete data. We contrast the possible use of (nonparametric) copula methods versus the problematic use of parametric copula models. For the latter, we stress, among other issues, the possibility of obtaining impossible models, arising from model misspecification or unidentifiability of the copula parameter.
LA - eng
KW - copula; discrete data; parametric model; statistical inference; unidentifiability
UR - http://eudml.org/doc/288496
ER -